Sleep quality, valence, energetic arousal, and calmness as predictors of device-based measured physical activity during a three-week mHealth intervention

Abstract

Physical inactivity is known to be a risk factor for several noncommunicable diseases and has a high prevalence in today’s society. Therefore, it is crucial to understand the psychological factors associated with physical activity (PA). Recent developments in the field of ambulatory assessment and technological advances are promising to enhance our understanding of this relationship by analyzing longitudinal data within- and between-persons. These analyses can reveal important factors to design behavior change interventions to enhance PA. Therefore, this study used an ecological momentary assessment during the 3‑week intervention period in the SMARTFAMILY2.0 trial and aimed to investigate whether valence, calmness, energetic arousal, and sleep quality predict daily steps and moderate to vigorous PA. Overall, 49 adults (35–60 years) and 40 children (5–19 years) were included in this analysis and self-rated their mental state within our smartphone application while also wearing a hip-worn accelerometer for 21 consecutive days (996 days included) during the intervention period. Multilevel analyses were conducted to predict daily PA while considering covariables (e.g., child/adult and non-wear time) both within- and between-persons. The results indicated that higher than average ratings of a person’s valence and energetic arousal on one day predicted increased PA while higher than average calmness predicted decreased PA at the same day within this person. Sleep quality and between-person effects of the affective states showed no clear associations to PA. Overall, these results showed that within-person associations of valence, calmness, and energetic arousal should be considered when designing PA interventions for both children and adults. The influence of sleep quality, as well as between-person effects, should be further explored by future studies.

A just-in-time adaptive intervention to enhance physical activity in the SMARTFAMILY2.0 trial.

“…Therefore, future studies should further investigate the reason for inactivity and consider adding it as user-input included in a decision rule at a decision point for the JITAI. Additionally, core affect might be an important aspect as it was related to daily PA in a previous examination within the same study (Fiedler et al, 2022). Here, valence and energetic arousal are known to be positively associated with PA while calmness is negatively associated with PA in adults (Forster et al, 2021) and children (Koch et al, 2018).…”

“…Overall, 98 participants were included in the intervention group of the SMART FAMILY 2.0 trial. The average number of days where the app was used for each participant was 17.39 out of 21, equating to 82.85% frequency of daily use (see elsewhere: Fiedler et al, 2022). Eighty-four of those participants received and answered at least one JITAI trigger during the 21-day intervention phase with a total of 1,274 answered JITAI triggers and were included in this examination.…”

“…However, by focusing on the momentary effects, the influences of other interventional aspects like the influence of providing information, and goal setting are assumed to be limited. Data of the same intervention period but different outcomes, namely, core affect and sleep quality values per day, has been used in a previous publication (Fiedler et al, 2022).…”

“…However, certain limitations need to be considered when interpreting the results of the current investigation. First, included adults and children were already quite active with around 8,000 steps and more than 50 min of moderate to vigorous PA per day on average while the app was used on 88% of the days (see Fiedler et al, 2022). This limited the number of triggers to be analyzed, especially for children.…”

Planting Seeds for the Future: Scoping Review of Child Health Promotion Apps for Parents

“…The lower number of the published studies during 2020 may be an influence of the COVID-19 pandemic, a trend that we saw increase in a swift subsequent spot search in each of the included databases (see Multimedia Appendix 1). Since this review was conducted, 3 additional study results from included study protocols were published [94][95][96]. The demand and need for addressing child health promotion have only grown since the start of the COVID-19 pandemic [97] and digital mHealth solutions are forecasted to continue to grow [98].…”